CN114326610A - AGV operation optimization system and method based on double-layer space-time network structure - Google Patents
AGV operation optimization system and method based on double-layer space-time network structure Download PDFInfo
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Abstract
The invention discloses an AGV operation optimization method based on a double-layer space-time network structure, which belongs to the technical field of AGV operation scheduling.A production execution master controller firstly leads in a production task, and the production execution master controller selects a task to be processed; the AGV dispatching equipment judges whether available idle AGV vehicles exist at the current moment, dispatches the idle AGV vehicles to reach the station area for goods taking, and sends the goods to the ex-warehouse area; when the AGV sends the goods to the ex-warehouse area, the AGV returns to the station area on the original way to put back the trays and the residual goods, and the station master controller updates the state of the AGV and waits for the next cycle task instruction. According to the method, the AGV is statically scheduled and a path planning scheme is adopted, so that the shortest execution time of each task and the shortest switching time between tasks are ensured, the specified carrying tasks are ensured to be completed in an automatic stereoscopic warehouse in a conflict-free, efficient and orderly manner, the problems of task assignment and operation sequence of the AGV in the work of the automatic stereoscopic warehouse are solved, and the AGV scheduling and path optimization in the automatic stereoscopic warehouse are realized.
Description
Technical Field
The invention belongs to the technical field of AGV operation scheduling, and particularly relates to an AGV operation optimization system and method based on a double-layer space-time network structure.
Background
The AGV system is a system composed of a plurality of AGVs operating independently, and as an important part in intelligent manufacturing, the AGV system is more and more widely applied in the logistics industry, and the work of a carrier is performed in a warehouse of each large company and a wharf of each port. At present, the demand of the AGV robot in China is vigorous day by day, and the AGV robot is mainly and intensively applied to the industries of production, logistics, routing inspection and the like. The production and manufacturing fields of the automobile industry, the household appliance manufacturing and the like are still the main demand market of the AGV in China, the demands of the two industries on the AGV are stable, but some defects exist in the aspects of management and application of the AGV, and many problems need to be solved: task scheduling problem: in order to complete the tasks orderly and efficiently, the system needs to reasonably distribute the tasks for each AGV, and the deadlock phenomenon is avoided in the process of completing the tasks. In some cases, an AGV may deliver multiple loads simultaneously, which requires a strict and orderly scheduling by the system, thereby improving the delivery efficiency. Second, the path selection problem: in an actual production environment, the routes available for the AGV to travel are complex and variable, and the selection of the optimal route requires a combination of time, path overlapping, and system efficiency to consider. In order to ensure that the AGVs do not have a conflict condition in the operation process, the system needs to monitor the AGVs in real time and dynamically adjust the traveling route.
At present, the dispatching of multiple AGVs mainly has two modes, firstly, tasks are reasonably allocated to each AGV according to the weight of the tasks, and then the tasks are delivered to a path planning system; and secondly, the system and the path planning system run cooperatively, and tasks are distributed to the AGVs by analyzing the running routes of the AGVs. The former only needs to consider the importance of the tasks for task allocation, and the latter needs to rely on a path planning system reversely for further optimization of the task allocation. At present, task scheduling and path planning are mostly discussed together, so that multiple aspects of the performance of the AGV, the priority of tasks, the optimal selection of paths and the like need to be comprehensively evaluated, evaluation methods of various indexes are different, and the method belongs to a multi-objective optimization type.
Disclosure of Invention
In order to overcome the problems that in the prior art, as an AGV system has the characteristics of more short-distance warehouse moving operation, more AGV conflicts, more structural corners of a goods shelf and the like, and the conflict-free AGV path planning scheme is difficult to obtain in a shorter time, the invention provides an AGV operation optimization system and method based on a double-layer space-time network structure, by adopting a static dispatching AGV and path planning scheme, the adjustment of the task continuing scheme reasonably distributes tasks for each AGV, ensures that the execution time of each task and the conversion time consumption among the tasks are shortest, reduces unnecessary time consumption caused by AGV path conflict, therefore, the total completion time is shortest, designated carrying tasks of the automatic stereoscopic warehouse are guaranteed to be completed in a conflict-free, efficient and orderly mode, the problems of task assignment and operation sequence of the AGV in the work of the automatic stereoscopic warehouse are solved, and the dispatching and path optimization of the AGV in the automatic stereoscopic warehouse are achieved.
The method and the system aim at the task scheduling problem of a multi-AGV system to carry out deep research, focus on research and analysis around a path planning and task scheduling system of the AGV, and try to combine the path planning and task allocation to carry out overall processing. The path planning allows slight deadlock to occur, analyzes several possible conflict situations in the AGV operation process, utilizes the scheduling system to perform coordinated planning on the paths of the AGVs, plans the optimal path for each AGV, and ensures that the AGVs operate smoothly and orderly in the path. The task allocation inherits the principle of balance, namely, under the condition that the system is guaranteed to finish tasks efficiently, the task number of each AGV is reasonably allocated, the balance of the task quantity among the AGVs is guaranteed, the task allocation is reevaluated according to the path planning result, the overall planning of the two systems is achieved, and the optimization of the whole AGV dispatching system is strived for.
The invention is realized by the following technical scheme:
an AGV operation optimization method based on a double-layer space-time network structure specifically comprises the following steps:
the method comprises the following steps: the production execution main control machine imports the production tasks, selects the order with the highest priority from the current order list as the task to be processed, and selects the order with the earliest order placing time as the task to be processed if the order priorities in the order list are the same; the production execution master control machine sends the transfer task to be processed to AGV dispatching equipment;
step two: the AGV dispatching equipment judges whether available idle AGV vehicles exist at the current moment, dispatches the idle AGV vehicles to reach the station area for goods taking, and sends the goods to the ex-warehouse area;
step three: when the AGV sends the goods to the ex-warehouse area, the AGV returns to the station area on the original way to put back the trays and the residual goods, and the station master controller updates the state of the AGV and waits for the next cycle task instruction.
Preferably, step two is as follows: and the AGV dispatching equipment identifies whether available idle AGV vehicles exist at the current moment, if so, the idle AGV closest to the task point is selected, and if not, the AGV capable of executing the task at the fastest speed is selected.
Preferably, the second step is specifically to find the shortest path from the current point of the idle AGV to the work station area through Dijkstra algorithm to pick up the goods, and find the shortest path from the work station area to the warehouse-out area through Dijkstra algorithm.
In a second aspect, the invention further provides an AGV operation system based on a double-layer space-time network structure, which comprises a production execution master control machine, AGV dispatching equipment, at least one AGV vehicle, a station master control machine, an operation dispatching server and a control server; the production execution master control machine, the AGV dispatching equipment, the operation dispatching server and the control server are mutually communicated through a network, and the AGV dispatching equipment is connected with AGV vehicles;
the control server is used for receiving and sending out a control instruction;
the job scheduling server is used for forming and sending job scheduling instructions.
Preferably, the system further comprises a control terminal connected with the control server, and the control terminal can be used for inputting or loading the multidimensional scheduling recorded information into the control server; and the control terminal can start the job scheduling task.
Preferably, the system further comprises a map server, the map server and the AGV dispatching equipment are mutually connected through the network, and the map server is used for storing and providing map information of the site.
Preferably, the AGV dispatching equipment is provided with a wireless communication module, and the AGV dispatching equipment is communicated with the AGV through the wireless communication module.
In a third aspect, the present invention provides a non-transitory computer readable storage medium having instructions that, when executed by a processor of a terminal, enable the terminal to perform a method for AGV operation optimization based on a two-tier spatiotemporal network structure according to the present invention.
Compared with the prior art, the invention has the following advantages:
1. the method has low cost, further expands the space of intelligent logistics unmanned warehouse, improves the automation rate, and promotes the quality improvement, cost reduction and efficiency improvement;
2. the reliability is strong, the control logic of the static scheduling mode is relatively clear, the stability is high, and safe and orderly warehouse operation is facilitated;
3. the efficiency is high, and the AGV system is ensured to carry out scheduling operation strictly and orderly, so that the warehouse can efficiently complete all designated carrying tasks;
4. the automation is high, and the task allocation is uniformly managed by the terminal system, so that the AGV can efficiently and orderly shuttle between workshops and warehouses.
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In order to more clearly illustrate the detailed description of the invention or the technical solutions in the prior art, the drawings that are needed in the detailed description of the invention or the prior art will be briefly described below. Throughout the drawings, like elements or portions are generally identified by like reference numerals. In the drawings, elements or portions are not necessarily drawn to scale.
FIG. 1 is a diagram of an AGV operation system based on a double-layer space-time network structure according to the present invention;
FIG. 2 is a schematic diagram of the AGV operation optimization method based on the double-layer space-time network structure according to the present invention;
FIG. 3 is a schematic diagram of the AGV runtime of the present invention;
FIG. 4 is a diagram of an AGV scheduling optimization spatiotemporal network of the present invention;
FIG. 5 is a schematic diagram of an AGV operation optimization method based on a double-layer space-time network structure according to embodiment 1 of the present invention;
FIG. 6 is a flowchart illustrating an AGV operation optimization method based on a double-layer space-time network structure according to the present invention;
Detailed Description
The following embodiments are only used for illustrating the technical solutions of the present invention more clearly, and therefore, the following embodiments are only used as examples, and the protection scope of the present invention is not limited thereby.
It is to be noted that, unless otherwise specified, technical or scientific terms used herein shall have the ordinary meaning as understood by those skilled in the art to which the invention pertains.
Example 1
As shown in fig. 6, this embodiment provides an AGV operation optimization method based on a double-layer spatio-temporal network structure, where the optimization method is implemented in pycharm software by using python programming language, and specifically includes the following steps:
the method comprises the following steps: the production execution main control machine imports the production tasks, selects the order with the highest priority from the current order list as the task to be processed, and selects the order with the earliest order placing time as the task to be processed if the order priorities in the order list are the same; the production execution master control machine sends the transfer task to be processed to AGV dispatching equipment;
step two: the AGV dispatching equipment judges whether available idle AGV vehicles exist at the current moment, dispatches the idle AGV vehicles to reach the station area for goods taking, and sends the goods to the ex-warehouse area;
step three: when the AGV sends the goods to the ex-warehouse area, the AGV returns to the station area on the original way to put back the trays and the residual goods, and the station master controller updates the state of the AGV and waits for the next cycle task instruction.
The second step is as follows: and the AGV dispatching equipment identifies whether available idle AGV vehicles exist at the current moment, if so, the idle AGV closest to the task point is selected, and if not, the AGV capable of executing the task at the fastest speed is selected.
And step two, specifically, finding the shortest path from the current position of the idle AGV to the work station area through a Dijkstra algorithm to pick up the goods, and finding the shortest path from the work station area to the warehouse-out area through the Dijkstra algorithm.
As shown in fig. 2, the present invention adopts a modeling method based on a double-layer space-time network structure, specifically, in the longitudinal direction, the time-space network is used to describe an AGV scheduling scheme and an AGV path selection scheme, and a mapping relationship between the two schemes is constructed, so as to perform collaborative optimization on the schemes.
The AGV dispatching method distributes tasks to AGV vehicles, determines the operation sequence, and does not directly appoint a specific running path of the AGV vehicles, thereby effectively making a decision on the AGV dispatching scheme and ensuring that all operation tasks are completed;
the running time required for the AGV to complete a task is shown in fig. 2. The scheduling waiting time is the time from the time when the scheduling system distributes tasks to a certain AGV receives the tasks and the system plans a path for the AGV; the operation task time is the time used by the AGV to travel from the current position to an operation task node of the scheduling system, and comprises the operation time and the moving time of the operation task; the task transfer time is the time taken by the AGV to travel from one job task node to another.
For the AGV scheduling problem, each operation position of a task is selected as a space node, and time is discretized to construct a "position-time" spatio-temporal network, as shown in fig. 3. Taking KLT warehouse-out task as an example, if the moving sequence of AGVs is "current position-task storage location-warehouse-out target position-task storage location", the task can be split into 4 space nodes, which respectively correspond to the target positions of the 4 operations, and the sequence of AGVs accessing each operation should strictly meet the operation process requirements.
Three operation arcs are involved in the space-time network:
(1) moving arcs in the task: representing a space-time arc of the AGV moving between different operation positions in the same operation task, wherein the corresponding duration of the space-time arc meets the requirement of the AGV moving between two adjacent operation tasks on the shortest walking time;
(2) operation arc in task: the method comprises the steps that the operation duration of an AGV at a certain target position is shown, the AGV does not move in space in the period, and the operation duration meets the requirement of the shortest operation time of operation corresponding to the target position;
(3) inter-task arc transfer: and the starting point of the space-time arc represents the space position corresponding to the final operation of the preorder task, the end point of the space arc represents the space position corresponding to the initial operation of the subsequent task, and the time consumed between the space position and the subsequent task meets the requirement of the shortest traveling time between the two positions.
Example 2
As shown in fig. 5, in the AGV operation optimization method based on the double-layer space-time network structure according to this embodiment, the number of ex-warehouses required is 4, the task start point is 1123, the task end point 1707, and the AGV needs to return to the 1123 position after completing the task; the method specifically comprises the following steps:
the method comprises the following steps: and (4) calling the idle AGV closest to the task point, and searching the shortest path from the current point of the AGV to the task point 1123 to execute the task by using a Dijkstra algorithm.
Step two: when the AGV reaches the designated goods taking point 1123, goods are extracted, and the shortest path 1707 from the task starting point 1123 to the warehouse-out point of the AGV is continuously searched through the Dijkstra algorithm.
Step three: after the AGV finishes the ex-warehouse task, the shortest path for the AGV to execute the task from the ex-warehouse point 1707 to the task terminal 1123 is found through the Dijkstra algorithm.
Step four: the AGV returns to position 1123, returns the remaining goods in the tray, ends the order, and continues to wait for the next task.
Example 3
As shown in fig. 1, the present embodiment provides an AGV operating system based on a double-layer space-time network structure, which includes a production execution master control machine, an AGV scheduling device, at least one AGV vehicle, a station master control machine, an operation scheduling server, and a control server; the production execution master control machine, the AGV dispatching equipment, the operation dispatching server and the control server are mutually communicated through a network, and the AGV dispatching equipment is connected with AGV vehicles;
the control server is used for receiving and sending out a control instruction;
the job scheduling server is used for forming and sending job scheduling instructions.
The system also comprises a control terminal connected with the control server, and multidimensional scheduling recorded information can be input or loaded into the control server through the control terminal; and the control terminal can start the job scheduling task.
The AGV dispatching system comprises a AGV dispatching device, and is characterized by further comprising a map server, wherein the map server and the AGV dispatching device pass through the network mutually, and the map server is used for storing and providing map information of a site.
The AGV dispatching equipment is provided with a wireless communication module, and the AGV dispatching equipment is communicated with AGV vehicles through the wireless communication module.
In an exemplary embodiment, a non-transitory computer readable medium comprising instructions, such as a memory comprising instructions, executable by a processor of the apparatus to perform the method for AGV operation optimization based on a two-tier spatiotemporal network architecture is also provided. For example, the non-transitory computer readable storage medium may be a ROM, a Random Access Memory (RAM), a CD-ROM, a magnetic tape, a floppy disk, an optical data storage device, and the like.
The preferred embodiments of the present invention have been described in detail with reference to the accompanying drawings, however, the present invention is not limited to the specific details of the above embodiments, and various simple modifications can be made to the technical solution of the present invention within the technical idea of the present invention, and these simple modifications are within the protective scope of the present invention.
It should be noted that the various technical features described in the above embodiments can be combined in any suitable manner without contradiction, and the invention is not described in any way for the possible combinations in order to avoid unnecessary repetition.
In addition, any combination of the various embodiments of the present invention is also possible, and the same should be considered as the disclosure of the present invention as long as it does not depart from the spirit of the present invention.
Claims (7)
1. An AGV operation optimization method based on a double-layer space-time network structure is characterized by specifically comprising the following steps:
the optimization method is realized in pychar software by using a python programming language, and the specific language execution steps are as follows:
the method comprises the following steps: the production execution main control machine imports the production tasks, selects the order with the highest priority from the current order list as the task to be processed, and selects the order with the earliest order placing time as the task to be processed if the order priorities in the order list are the same; the production execution master control machine sends the transfer task to be processed to AGV dispatching equipment;
step two: the AGV dispatching equipment judges whether available idle AGV vehicles exist at the current moment, dispatches the idle AGV vehicles to reach the station area for goods taking, and sends the goods to the ex-warehouse area;
step three: when the AGV sends the goods to the ex-warehouse area, the AGV returns to the station area on the original way to put back the trays and the residual goods, and the station master controller updates the state of the AGV and waits for the next cycle task instruction.
2. The AGV operation optimization method based on the double-layer space-time network structure as claimed in claim 1, wherein the second step is as follows: and the AGV dispatching equipment identifies whether available idle AGV vehicles exist at the current moment, if so, the idle AGV closest to the task point is selected, and if not, the AGV capable of executing the task at the fastest speed is selected.
3. The AGV operation optimization method based on the double-layer space-time network structure as claimed in claim 1, wherein in the second step, the Dijkstra algorithm is used to find the shortest path from the current point of the empty AGV to the work area for picking up the goods, and the Dijkstra algorithm is used to find the shortest path from the work area of the AGV to the warehouse-out area.
4. An AGV operation system based on a double-layer space-time network structure is characterized by comprising a production execution master control machine, AGV dispatching equipment, at least one AGV vehicle, a station master control machine, an operation dispatching server and a control server; the production execution master control machine, the AGV dispatching equipment, the operation dispatching server and the control server are mutually communicated through a network, and the AGV dispatching equipment is connected with AGV vehicles;
the control server is used for receiving and sending out a control instruction;
the job scheduling server is used for forming and sending job scheduling instructions.
5. The AGV operation system according to claim 4, further comprising a control terminal connected to the control server, wherein the control terminal is capable of inputting or loading multidimensional scheduling history information into the control server; and the control terminal can start the job scheduling task.
6. The AGV operation system according to claim 4, further comprising a map server, wherein the map server and the AGV dispatching device are connected to each other through the network, and the map server is used for storing and providing map information of a lot.
7. The AGV operation system based on the double-layer space-time network structure according to claim 4, wherein a wireless communication module is provided on the AGV dispatching device, and the AGV dispatching device communicates with the AGV vehicles through the wireless communication module.
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